docstr: Evaluate on x, y
  :param x: input
  :param y: target
  :param metrics: a list of metrics in string format
  :param multioutput: output mode
  :return: a list of metric evaluation results
docstr_tok: ["Evaluate","on","x",",","y",":","param","x",":","input",":","param","y",":","target",":","param","metrics",":","a","list","of","metrics","in","string","format",":","param","multioutput",":","output","mode",":","return",":","a","list","of","metric","evaluation","results"]
code: def evaluate(
      self,
      x,
      y,
      batch_size=32,
      metrics=["mse"],
      multioutput="raw_values",
  ):
      """
      Evaluate on x, y
      :param x: input
      :param y: target
      :param metrics: a list of metrics in string format
      :param multioutput: output mode
      :return: a list of metric evaluation results
      """
      y_pred = self.predict(x, batch_size=batch_size)
      return [
          Evaluator.evaluate(m, y, y_pred, multioutput=multioutput)
          for m in metrics
      ]
  
imports: from bigdl.orca.automl.model.abstract import BaseModel, ModelBuilder
  import numpy
  from bigdl.orca.automl.metrics import Evaluator
  from bigdl.orca.common import SafePickle
  import copy
  import tensorflow
  from tensorflow.keras import backend
  import types
  from bigdl.dllib.utils.log4Error import *
label_desc: Use image node_id 5 for calling the KerasBaseModel obj's underlying member method code with example usage: obj.evaluate(x, y, batch_size, metrics, multioutput) and returns: unknown